EMG RMS Time Interval Calculations

Question

Parth T.A. 2020-7-30

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https://ww2.mathworks.cn/matlabcentral/answers/572821-emg-rms-time-interval-calculations

评论： dpb 2020-7-31

I am writing code to analyze EMG data and need to specifically measure the RMS envelope of the signal. After this, I need to analyze each prominent envelope's duration/time interval and the RMS value within that envelope itself. I already obtained the general RMS envelope of the signal, but I can't isolate the envelopes that matter and calucate their RMS values. How can I accomplish this?

Below is my code:

%% load data
[filename, path, sureORcancel] = uigetfile('.mat', 'Choose the data for processing');
data = load(strcat(path,filename));
names = fieldnames(data);
EMG_valuesO = data.(names{9,1}).values;     %the EMG values data
EMG_values = doFilter(EMG_valuesO);
%define the sampling rate
sampling_rate = 1000;
length_EMG_values = length(EMG_values);
time = [0:1:length_EMG_values-1] * (1/sampling_rate);
figure
plot(time, EMG_values)
% find the peaks of EMG_signals, both postive peaks and negtive peaks
[EMG_values_pks_pos,EMG_values_locs_pos] = findpeaks(EMG_values, 'minpeakheight', 0.1);
[EMG_values_pks_neg,EMG_values_locs_neg] = findpeaks(-EMG_values, 'minpeakheight', 0.1);
%% combine them together
EMG_values_locs = [EMG_values_locs_pos; EMG_values_locs_neg];
[EMG_values_locs, index] = sort(EMG_values_locs);
EMG_values_pks = [EMG_values_pks_pos; -EMG_values_pks_neg];
EMG_values_pks = EMG_values_pks(index);
timediff = [];
% window length is 200 points(0.1s)
RMS = [];
RMS_time = [];
for i = 1:length(EMG_values_locs)-1
    EMG_values_samples = EMG_values(EMG_values_locs(i):EMG_values_locs(i)+199);
    %find the low peaks
    if EMG_values_pks(i) > 0    %the high peak value is a postive value
        [Minus_EMG_values_samples_pks,Minus_EMG_values_samples_locs] = findpeaks(-EMG_values_samples, 'SortStr','descend');
    else                            %the high peak value is a negtive value
        [Minus_EMG_values_samples_pks,Minus_EMG_values_samples_locs] = findpeaks(EMG_values_samples, 'SortStr','descend');
    end
    % figure
    % findpeaks(-EMG_values_samples, 'SortStr','descend')
    % extract the data between high peak and low peak
    RMS_EMG_values_samples = EMG_values_samples(1:Minus_EMG_values_samples_locs(1));
    RMS = [RMS, rms(RMS_EMG_values_samples)]; 
    RMS_time = [RMS_time, EMG_values_locs(i)];
end
xlsx_filename = strrep(filename, '.mat', '.xlsx');
xlswrite(strcat(path,xlsx_filename),[RMS_time; RMS]');
figure;
envelope (EMG_values, 1000, 'rms');
function y = doFilter(x)
%DOFILTER Filters input x and returns output y.
% MATLAB Code
% Generated by MATLAB(R) 9.8 and DSP System Toolbox 9.10.
% Generated on: 25-Jul-2020 18:24:50
  persistent Hd;
  if isempty(Hd)
    N      = 2;     % Order
    Fpass1 = 30;    % First Passband Frequency
    Fpass2 = 100;   % Second Passband Frequency
    Astop1 = 60;    % First Stopband Attenuation (dB)
    Apass  = 1;     % Passband Ripple (dB)
    Astop2 = 60;    % Second Stopband Attenuation (dB)
    Fs     = 1000;  % Sampling Frequency
    h = fdesign.bandpass('n,fp1,fp2,ast1,ap,ast2', N, Fpass1, Fpass2, ...
        Astop1, Apass, Astop2, Fs);
    Hd = design(h, 'ellip', ...
        'SOSScaleNorm', 'Linf');
    set(Hd,'PersistentMemory',true);
  end
  y = filter(Hd,x);
end

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dpb 2020-7-31

Only way anybody could do anything to help here would be to have data to see and for you to illustrate what it is you have and are trying to isolate...

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